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This paper aims to examine the association between regulatory capital and risk of Indian commercial banks and the impacts of other relevant variables on them.

The study is based on a secondary data set on Indian commercial banks collected from “Capitaline Plus” corporate database and annual reports of the respective banks. Total 41 major Indian banks (21 public and 20 private sector banks) are considered in this study. Here absolute values of capital and risk are used as dependent variables along with some relevant bank specific explanatory variables in a system of a two-equation model. Based on the nature of interrelationship and identifiability of the equations, three-stage least squares (3SLS) technique is used to estimate the relationship.

Risk and capital of Indian commercial banks are inversely associated. The influence of profitability on both capital and risk is significantly positive. Moreover, human capital efficiency is negatively associated with the undertaking of risk by the banks. In this respect, Indian private sector banks are found to be more efficient in utilizing human capital for reducing credit risk.

It is the first comparative study in India examining the relationship between capital and risk of Indian public and private sector commercial banks covering both Basel I and II periods. Further, the role of human resource in managing risk is considered as a relevant variable in this study.

This research aims to model the relationship between the credit risk signals in the credit default swap (CDS) market and agency credit ratings, and determines the factors that help explain the variation in such signals.

A comprehensive analysis of the differences in the relative credit risk assessments of CDS-based risk signals and agency ratings is provided. It is shown that the divergence between credit risk signals in the CDS market and agency ratings is explained by factors which the rating agencies may consider differently than credit market participants.

The results suggest that agency credit ratings of relative riskiness of a reference entity do not always correspond with assessments by CDS spreads, as the price of risk is a function of additional macro and micro factors that can be explained using statistical analysis.

This research is unique in modeling the relationship between the credit risk assessments of the CDS market and the agency ratings, which to the best of the authors' knowledge has not been analyzed before in terms of their agreement and the level of discrepancy between them. This model can be used by investors in debt instruments that are not explicitly CDSs or which have illiquid CDS contracts, to replicate market-based, point-in-time credit risk signals. Based on both market-based and firm-specific factors in this model, the results can be used to augment through-the-cycle credit risk assessments, analyze issues surrounding the pricing of CDSs and examine the policies of credit rating agencies.

The purpose of this study was to examine the 2007-2009 financial crisis to analyze how securitization relates to the Italian bank risk profile, both in terms of credit and liquidity risks.

To test our research hypotheses, we adopt ordered probit models, in which we regress the changes in credit risk and liquidity on a set of regressors, including two securitization dummy variables plus a vector of control variables.

Our results show that the impact of securitization on the originators risk-taking is not uniform. When credit risk is considered, the securitization effects seem to be statistically significant only during the crisis period. However, when we turn to analyze the bank’s liquidity position, our results show that securitization improves it both during the pre-crisis and the crisis years. Our results support the Basel III initiatives aimed to realize a better integration between the different types of risks (i.e. credit and liquidity risks).

The major limitation of our study is related to the analyzed geographic area.

First, our results support the Basel III initiatives aimed to realize a better integration between the different types of risks (i.e. credit and liquidity risks). In general, the broad policy implication of the paper is that in some contexts, such as the Italian market, securitization does not necessarily produce negative effects in terms of bank’s risk.

This study contributes to the empirical literature on the effects of securitization for banks in several ways. First, we consider the complexity of the bank’s risk profile; second, despite the importance of the Italian securitization market, there is a research void on it. Furthermore, unlike previous studies, our analysis covers the period 2000-2009, including the financial crisis years. Finally, to our knowledge, our methodology (ordered probit models) has not been used in the past in this context.

This study examines the impact of chief executive officer (CEO) power, institutional investors and their interaction on green financing provided by Bangladeshi financial institutions and the moderating effect of government policy and CEO political connections on these relations.

We employ ordinary least squares (OLS) regressions and interaction terms among variables of interest for the empirical analysis.

Green financing decreases with CEO power, implying that CEOs of this country’s financial institutions are averse to green loans, whereas institutional investors increase green financing extended by these institutions. The government policy, which includes financial incentives for complying financial institutions, strengthens institutional investors' positive impact on green financing, but it does not change CEOs' aversion to green loans. Institutional investors have a positive moderating effect on the relationship between green finance (GF) and CEO power, but this positive moderating effect is negated in banks where the government owns a stake, possibly because CEOs of state-owned financial institutions are politically connected, which reduces institutional investors’ influence over them.

This study is unique in that it is the first to examine how the interaction among different stakeholders affects green financing in a unique setting. As the literature is almost silent on this topic, the findings of this paper are expected to raise policymakers’ awareness of the obstacles that hamper the efforts of developing countries to go green.

With multiple-related organizations, worldwide infections, deep economic recession and public disorder, and large consumption amount of anti-epidemic resources, the coronavirus disease 2019 (COVID-19) has been defined as a public health emergency of international concern (PHEIC). Nowadays, Wuhan has recovered from the pandemic disaster and reentered normalization. The purposes of this study are to (1) summarize organization collaboration patterns, successful experience and latent defects under across-stage evolution of Wuhan's cooperation governance mode against the pandemic, and on the basis, (2) reveal how the COVID-19 development trends and organizations' collaborative behaviors affected each other.

Detailed content analysis of online news reports covering COVID-19 prevention and control measures on the website of Wuhan Municipal Government was adopted to identify organizations and their mutual collaborative interrelationships. Four complex network (CN) models of organization collaboration representing the outbreak, preliminary control, recession and normalization stages, respectively, were established then. Time-span-based dynamic parameter analyses of the proposed networks, comprising network cohesiveness analysis and node centrality analysis, were undertaken to indicate changes of global and local characteristics in networks.

First, the definite collaborative status of Wuhan Headquarters for Pandemic Prevention and Control (WHPPC) has persisted throughout the period. Medical institutions and some other administrations were the most crucial participants collaborating with the WHPPC. Construction-industry organizations altered pandemic development trends twice to make the situation controllable. Media, large-scale enterprises, etc. set about underscoring themselves contributions since the third stage. Grassroots cadres and healthcare force, small and medium-sized enterprises (SMEs), financial institutions, etc. were essential collaborated objects. Second, four evolution mechanisms of organization collaboration responding to the COVID-19 in Wuhan has been proposed.

First, universality of Wuhan-style governance experience may be affected. Second, the stage-dividing process may not be the most appropriate. Then, data source was single and link characteristics were not considered when modeling.

This study may offer beneficial action guidelines to governmental agencies, the society force, media, construction-industry organizations and the market in other countries or regions suffering from COVID-19. Other organizations involved could also learn from the concluded organizations' contributions and four evolution mechanisms to find improvement directions.

This study adds to the current theoretical knowledge body by verifying the feasibility and effectiveness of investigating cooperation governance in public emergencies from the perspectives of analyzing the across-stage organization collaboration CNs.

Big 4 professional services firms increasingly lay claim to recruiting and including staff of diverse genders, cultures, ages and sexualities. Drawing on Foucauldian insights, this study explores how LGBTIQ+ staff navigated shifting technologies of client power, at the time marriage equality was legislated in Australia.

This article explores changing experiences of LGBTIQ+ staff and allies, through 56 semi-structured interviews undertaken through 2018–2019.

Technologies of client power were central to shaping workplace experiences for LGBTIQ+ staff. However, each firm was also keen to carve unique and bold responses to changing societal attitudes regarding sexuality and gender. These progressive moves did not sit comfortably with all clients, and so this article provides insight into the limitations of client privilege within professional services firms. For staff, this increasing complexity of sometimes opaque, contradictory and shifting technologies of client and firm power, enabled agency to explore a sense of self for some, but continued to exclude others.

Little attention has been directed to exploring challenges for staff of sexual and gendered diversity within professional services firms, or to exploring how staff navigate changing perceptions of client power.

Construction projects in Malaysia are often delayed and over budget due to heavy reliance on labor. Linear regression (LR) models have been used in most labor cost (LC) studies, which are less accurate than machine learning (ML) tools. Construction management applications have increasingly used ML tools in recent years and have greatly impacted forecasting. The research aims to identify the most influential LC factors using statistical approaches, collect data and forecast LC models for improved forecasts of LC.

A thorough literature review was completed to identify LC factors. Experienced project managers were administered to rank the factors based on importance and relevance. Then, data were collected for the six highest ranked factors, and five ML models were created. Finally, five categorical indices were used to analyze and measure the effectiveness of models in determining the performance category.

Worker age, construction skills, worker origin, worker training/education, type of work and worker experience were identified as the most influencing factors on LC. SVM provided the best in comparison to other models.

The findings support data-driven regulatory and practice improvements aimed at improving labor issues in Malaysia, with the possibility for replication in other countries facing comparable problems.

The study focuses on influential factors of collaboration on government data security by the Chinese government.

The article explores the case of e-government in the Chinese centralized unitary state system context, using a structured–pragmatic–situational (SPS) approach and the boundary theory as an analytical lens.

The findings indicate that e-government operates in highly interconnected environments where the safe flow of government data requires collaborative and cross-boundary strategies. Any organization is a potential “weakest link”. In addition, collaboration is fragmented by ambiguous accountability and organizational inertia across government departments, resources differences and limited visibility and measurability of security efforts across government levels and conflicts and uncertainties in principal–agent relationships. The solutions for those obstacles are also discussed from the multi-function, multi-level and multi-actor dimensions, respectively. A multi-dimensional overarching security model for the flow of government data is proposed.

The study advances the technology-oriented micro-analysis of previous studies on government data security to cross-organizational revealing at the macrolevel by connecting streams of research in information systems and public administration. These findings will contribute to making the safe flow of government data more resilient in the transformation of e-government.